What is Kol Sentitment Mcp

kol-sentitment-mcp is a Model Context Protocol (MCP) implementation designed for Key Opinion Leader (KOL) sentiment analysis using the Masa AI API. It provides a standardized interface for AI assistants to analyze KOLs on social media platforms.

Use cases

Use cases include monitoring KOL sentiment for brand partnerships, analyzing public opinion on social media campaigns, identifying trending topics among KOLs, and generating insights for market research.

How to use

To use kol-sentitment-mcp, clone the repository, set up a Python virtual environment, install the required dependencies, configure the .env file with your Masa API key, and start the server using the command ‘python run.py’.

Key features

Key features include searching for KOL content across platforms, analyzing sentiment of KOL posts, extracting trending topics, generating comprehensive sentiment analysis, identifying trends across multiple KOLs, supporting both live and historical data, secure API access, and detailed logging.

Where to use

kol-sentitment-mcp can be used in marketing, social media analysis, public relations, and any field that requires understanding public sentiment towards Key Opinion Leaders.

KOL Sentiment MCP

A Model Context Protocol (MCP) implementation for Key Opinion Leader sentiment analysis using the Masa AI API.

Overview

KOL Sentiment MCP provides a standardized interface for AI assistants to analyze Key Opinion Leaders (KOLs) on social media platforms. It leverages the Masa AI API for powerful semantic search and data retrieval, allowing for sentiment analysis, topic extraction, and trend identification without direct API access.

Features

• Search for KOL content across platforms
• Analyze sentiment of KOL posts
• Extract trending topics from KOL content
• Generate comprehensive KOL sentiment analysis
• Identify trends across multiple KOLs
• Support for both live and indexed (historical) data
• Secure and rate-limited API access
• Detailed logging and error handling

Installation

Prerequisites

• Python 3.9+
• pip

Setup

1. Clone the repository:

   git clone https://github.com/olaxbt/kol-sentiment-mcp.git
   cd kol-sentiment-mcp
   

2. Create and activate a virtual environment:

   python -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate
   

3. Install dependencies:

   pip install -r requirements.txt
   

4. Create a .env file based on .env.example:

   cp .env.example .env
   

5. Edit the .env file to add your Masa API key and other settings.

Usage

Starting the Server

python run.py

The server will start on the port specified in your .env file (default: 5000).

API Endpoints

• GET / - Welcome page with service information
• GET /health - Health check endpoint
• GET /api/mcp/ping - MCP service health check
• POST /api/mcp/query - Main MCP query endpoint

MCP Actions

The KOL Sentiment MCP supports the following actions:

1. kol.search - Search for KOL content
2. kol.sentiment - Analyze sentiment of KOL content
3. kol.topics - Extract topics from KOL content
4. kol.insights - Get comprehensive insights about a KOL
5. kol.trends - Analyze trends across multiple KOLs

Example Queries

Search for KOL Content

{
  "id": "request123",
  "action": "kol.search",
  "params": {
    "query": "cryptocurrency",
    "kol_username": "elonmusk",
    "search_type": "indexed",
    "max_results": 10
  }
}

Analyze KOL Sentiment

{
  "id": "request123",
  "action": "kol.sentiment",
  "params": {
    "query": "AI",
    "kol_username": "elonmusk",
    "search_type": "indexed",
    "max_results": 20
  }
}

Get Comprehensive KOL Insights

{
  "id": "request123",
  "action": "kol.insights",
  "params": {
    "username": "elonmusk",
    "query": "",
    "search_type": "indexed",
    "max_results": 20
  }
}

Analyze Trends Across Multiple KOLs

{
  "id": "request123",
  "action": "kol.trends",
  "params": {
    "usernames": [
      "elonmusk",
      "VitalikButerin",
      "SBF_FTX"
    ],
    "query": "blockchain",
    "search_type": "indexed",
    "max_results_per_kol": 10
  }
}

Development

Project Structure

kol-sentiment-mcp/
├── app/
│   ├── handlers/        # Action handlers
│   ├── routes/          # API routes
│   ├── services/        # Core services
│   ├── templates/       # HTML templates
│   └── utils/           # Utilities
├── logs/                # Log files
├── tests/               # Test cases
├── .env                 # Environment variables
├── .env.example         # Example environment file
├── requirements.txt     # Dependencies
├── run.py               # Main entry point
└── README.md            # Documentation

License

MIT

Acknowledgements

• Masa AI API for X/Twitter data retrieval
• Model Context Protocol for standardized AI interaction